Thanks.

Thanks,
Steve

Thanks…

Steve Mc: No one’s thrown any stones at this calculation. Now these are not randomly chosen from the PC1s but were selected to illustrate high-end. But I suspect that, if you selected 14 at random from the population and flipped them to ensure orientation, and then applied O&B methods, you’d get results similar to O&B. It would be a useful exercise. I’ve kept all the simulated PC1s but they are 50 MB in size, although in 10 5 MB packages.

Very interesting plots.

Like all living things, genetics also plays a very important part in tree growth rates, density, etc. Therefore, you can probably find a tree to prove anything you want to.

Also interesting is that when I look at the corresponding ring width and density data sets, some of them seem to have very good correlation, such as Az555/Az555x and Az554/Az554x but others like Az553/Az553x have what look like no or negative correlation. Perhaps what is happening is, if the soil is good and precipitation is plenty, higher (lower?) temperatures are allowing the trees to make wider AND denser rings, whereas in other areas the soil is bad or precipitation is poor, and higher (lower?) temperatures are allowing for wider rings, but no more density can be achieved – and in some cases lower. That’s just a guess, but it seems like there must be some process determining whether there is good correlation between the two attributes, or not.

None of the Ca width/density comparisons look to me like a negative correlation but overall the correlation doesn’t seem to be as strong as those two Az series, which look almost identical between the width and density graphs in terms of shape.

Here’s a graph of the first ten in the CA series, with their average below, to demonstrate that the “hockey-stick” shape is not common to many of these series. It’s in a few out of hundreds, from what I have seen so far, but it’s of such great magnitude that it tends to dominate the shape of the average of a large number of the data series. I can’t imagine how much effect weighting those particular proxies by 80% or more must have on the final result.

They’re actually dynamically generated graphs, you can change what they draw yourself if you want to fiddle with it.

I can’t work out what’s going on. Perhaps “x” indicates that the original authors published a new set of data based on additional trees? Some of them just seem to have been renormalized between the non-x/x series, whereas others look quite different. Ca556x seems a bit odd, I’ve graphed it down the bottom, it starts out really far into the negative zone – perhaps because it’s based on a tree which started growing around the start of the series, maybe in a bad location, so didn’t do well at first.

You graphed Az553x/554x/555x; did you also graph Az553/554/555. It would be interesting to see what Mann did here.

Correction: When I said “North-West USA” I meant “Western Northern America”, which is not quite the same thing. I guess “Western USA” is a better description, since I don’t see any Canadian sites.